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Sistema de Recomendación de Matrículas en Asignaturas Basados en Perfiles de Docentes, Alumnos y Asignaturas en la Escuela Profesional de Ingeniería de Sistemas de la Universidad Nacional de San Agustín | ||
| Published in: | Innovation in Education and Inclusion : Proceedings of the 16th LACCEI International Multi-Conference for Engineering, Education and Technology |  |
| Date of Conference: | July 18-20, 2018 | |
| Location of Conference: | Lima, Perú | |
| Authors: |
Eveling Castro Gutierrez (Universidad Nacional de San Agustín, PE) Jerson Erick Herrera Rivera (Universidad Nacional de San Agustín, PE) | |
| Full Paper: | #127 | |
Abstract:One of the main problems faced by university students (specifically the case of the Professional School of Systems Engineering of the National University of San Agustín) is to make the right decision in relation to the subjects to be enrolled based on available information (subjects, syllabus, schedules, content of the subject, teacher, and others), a situation that can be generalized in all universities. Under these circumstances, this research work seeks to develop a Recommendation System based on mining techniques that will give students the support to choose which subjects they should enroll in and obtain better results in the academic field. The recommendation given will be based on the previous experience obtained from each student enrollment. With the information obtained, a student profile, a subject profile and, as far as possible, a teacher profile are created. To reach the objective, data has been analyzed of the students of the aforementioned school, between 2011 and 2016. The results obtained indicate that data mining techniques (algorithms based on rules and tree-based algorithms) do not adequately represent the attributes of teachers or of subjects, unlike the models of recommendation systems (collaborative models and content-based models) | ||